EGG2017: Innovate. Get Ahead. Disrupt. And Embrace Non-Conformity.
On November 30th 2017, there’s a new kind of data science & analytics conference: EGG2017, Dataiku’s first large-scale data science and analytics conference in New York, NY.
On November 30th 2017, there’s a new kind of data science & analytics conference: EGG2017, Dataiku’s first large-scale data science and analytics conference in New York, NY. EGG2017 is about breaking free from what's always been done and enabling what's new. Get real-world examples and insights on developing data-driven organizations from industry-leading players including:
- Walid Mehanna - Head of Data & Analytics Mercedes-Benz Cars @ Daimler AG
- Chris Kakkanatt - Data Science Team lead @ Pfizer
- Mayur Thakur - Managing Director @ Goldman Sachs
EGG2017 aims to bring together pioneers and visionaries of the data ecosystem to welcome and accelerate the next generation of truly data-driven decision making for the enterprise.
What to Expect?
This isn’t just any corporate data science or analytics conference - after all, it’s named it EGG.
Why EGG? Because we pride ourselves on breaking free from conventionality.
Specifically, EGG2017 will be about:
- Real use cases from real data teams at real companies, from startups to large enterprises and Fortune 500s.
- Bringing together leaders in analytics, data science, and machine learning.
- Best practices of productive and scalable data teams across industries.
- Practical insight and concrete next steps to going from raw data to insights and predictions.
Has Your Interest Been Piqued?
Great! Here’s some high-level logistical details. You can also find more on the EGG2017 site.
November 30, 2017
Day-long event (8:30 a.m. to 6:30 p.m.)
In New York City
Morning sessions and panel discussions by Fortune 100 Industry Leaders on scaling data analytics across the enterprise.
Afternoon sessions in two separate tracks:
- Track one: Data Science for Experts: Attendees will deep dive into topics running from Infrastructure and Security to automation and AI to Graph Analytics and Deep Learning.
- Track Two: When Data Science & Business Collide: Sessions here will explore real-life business applications in marketing, retail, banking, insurance, and manufacturing.
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